The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data
Clustering algorithms can be used to create an outlier detection procedure in univariate circular data. The circular distance between each point of angular observation in circular data is used to calculate the similarity measure to appropriately group observations. In this paper, we present a cluste...
Main Authors: | Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff |
---|---|
Format: | Article |
Language: | English |
Published: |
PJSOR
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/35453/1/Zulkipli%20et%20al.%20PJSOR.pdf |
Similar Items
-
A synthetic data generation procedure for univariate circular data with various outliers scenarios using Python programming language
by: Nur Syahirah, Zulkipli, et al.
Published: (2021) -
Comparative study of clustering-based outliers detection methods in circularcircular regression model
by: Siti Zanariah, Satari, et al.
Published: (2021) -
Graphical Summaries of Circular Data with Outliers Using Python Programming Language
by: Nur Syahirah, Zulkipli, et al.
Published: (2021) -
Descriptive analysis of circular data with outliers using Python programming language
by: N. S., Zulkipli, et al.
Published: (2020) -
A new single linkage robust clustering outlier detection procedures for multivariate data
by: Sharifah Sakinah, Syed Abd Mutalib, et al.
Published: (2023)